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Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach

Published online by Cambridge University Press:  06 April 2009

Christopher Neely ,
Paul Weller  and
Rob Dittmar
Christopher Neely
Affiliation:
Research Department, Federal Reserve Bank of St. Louis, St. Louis, MO 63011
Paul Weller
Affiliation:
Department of Finance, College of Business Administration, University of Iowa, Iowa City, IA 52242.
Rob Dittmar
Affiliation:
Research Department, Federal Reserve Bank of St. Louis, St. Louis, MO 63011
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Abstract

Using genetic programming techniques to find technical trading rules, we find strong evidence of economically significant out-of-sample excess returns to those rules for each of six exchange rates over the period 1981–1995. Further, when the dollar/Deutsche mark rules are allowed to determine trades in the other markets, there is significant improvement in performance in all cases, except for the Deutsche mark/yen. Betas calculated for the returns according to various benchmark portfolios provide no evidence that the returns to these rules are compensation for bearing systematic risk. Bootstrapping results on the dollar/Deutsche mark indicate that the trading rules detect patterns in the data that are not captured by standard statistical models.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 32 , Issue 4 , December 1997 , pp. 405 - 426
Copyright
Copyright © School of Business Administration, University of Washington 1997

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